Tuberculosis (TB) has one of the highest mortality rates among infectious diseases worldwide. The immune response in the host after infection is proposed to contribute significantly to the progression of TB, but the specific mechanisms involved remain to be elucidated. Single-cell RNA sequencing (scRNA-seq) provides unbiased transcriptome sequencing of large quantities of individual cells, thereby defining biological comprehension of cellular heterogeneity and dynamic transcriptome state of cell populations in the field of immunology and is therefore increasingly applied to lung disease research. Here, we first briefly introduce the concept of scRNA-seq, followed by a summarization on the application of scRNA-seq to TB. Furthermore, we underscore the potential of scRNA-seq for clinical biomarker exploration, host-directed therapy, and precision therapy research in TB and discuss the bottlenecks that need to be overcome for the broad application of scRNA-seq to TB-related research.
Humans ; Single-Cell Analysis/methods* ; Tuberculosis/genetics* ; Sequence Analysis, RNA/methods* ; Transcriptome/genetics*

BACKGROUND: Several studies have demonstrated the occurrence of secondary tumors as a rare but significant complication of chimeric antigen receptor T (CAR-T) cell therapy, underscoring the need for a detailed investigation. Given the limited variety of secondary tumor types reported to date, a comprehensive characterization of the various secondary tumors arising after CAR-T therapy is essential to understand the associated risks and to define the role of the immune microenvironment in malignant transformation. This study aims to characterize the immune microenvironment of a newly identified secondary tumor post-CAR-T therapy, to clarify its pathogenesis and potential therapeutic targets. METHODS: In this study, the bone marrow (BM) samples were collected by aspiration from the primary and secondary tumors before and after CD19 CAR-T treatment. The CD45 + BM cells were enriched with human CD45 microbeads. The CD45 + cells were then sent for 10× genomics single-cell RNA sequencing (scRNA-seq) to identify cell populations. The Cell Ranger pipeline and CellChat were used for detailed analysis. RESULTS: In this study, a rare type of secondary chronic myelomonocytic leukemia (CMML) were reported in a patient with diffuse large B-cell lymphoma (DLBCL) who had previously received CD19 CAR-T therapy. The scRNA-seq analysis revealed increased inflammatory cytokines, chemokines, and an immunosuppressive state of monocytes/macrophages, which may impair cytotoxic activity in both T and natural killer (NK) cells in secondary CMML before treatment. In contrast, their cytotoxicity was restored in secondary CMML after treatment. CONCLUSIONS This finding delineates a previously unrecognized type of secondary tumor, CMML, after CAR-T therapy and provide a framework for defining the immune microenvironment of secondary tumor occurrence after CAR-T therapy. In addition, the results provide a rationale for targeting macrophages to improve treatment strategies for CMML treatment.
Humans ; Lymphoma, Large B-Cell, Diffuse/therapy* ; Tumor Microenvironment/genetics* ; Antigens, CD19/metabolism* ; Leukemia, Myelomonocytic, Chronic/genetics* ; Immunotherapy, Adoptive/adverse effects* ; Male ; Single-Cell Analysis/methods* ; Female ; Sequence Analysis, RNA/methods* ; Receptors, Chimeric Antigen ; Middle Aged

Over the past decade, high-throughput RNA sequencing (RNA-seq) has vastly expanded our understanding of transcriptome dynamics in human physiology and disease. As a powerful tool for investigating systematic changes in RNA biology, RNA-seq has facilitated the discovery of novel functional RNA species. Mature RNA transcripts, which transmit genetic information from DNA to proteins, undergo intricate transcriptional and post-transcriptional regulation. This process allows a single gene to produce multiple RNA transcripts, each performing specific functions depending on the physiological or pathological context. Specific RNA transcripts (SRTs) are uniquely expressed in particular tissues or tumors and are closely associated with tissue-specific functions or disease states, particularly cancer. This review explores the generation of SRTs through key mechanisms, such as alternative splicing (AS), transcriptional regulation, polyadenylation (polyA), and the influence of transposable elements (TEs). We also examine their critical roles in normal tissue development and diseases, with an emphasis on their relevance to cancer. Furthermore, the potential applications of SRTs in diagnosing and treating diseases, especially malignancies, are discussed. By serving as diagnostic markers and therapeutic targets, SRTs hold significant promise in the development of personalized medicine and precision therapies. This review aims to provide new insights into the importance of SRTs in advancing the understanding and treatment of human diseases.
Humans ; Neoplasms/genetics* ; Alternative Splicing/genetics* ; RNA/genetics* ; Animals ; Sequence Analysis, RNA/methods* ; Polyadenylation/genetics*

Humans ; Consensus ; High-Throughput Nucleotide Sequencing/standards* ; Neoplasms/diagnosis* ; Quality Control ; Sequence Analysis, DNA/methods* ; Sequence Analysis, RNA/methods*

OBJECTIVES: Recent advancements in single-cell RNA sequencing (scRNA-seq) have revolutionized the study of cellular heterogeneity, particularly within the hematological system. However, accurately annotating cell types remains challenging due to the complexity of immune cells. To address this challenge, we develop a PAN-blood single-cell Data Annotator (scPANDA), which leverages a comprehensive 10-million-cell atlas to provide precise cell type annotation. METHODS: The atlas, constructed from data collected in 16 studies, incorporated rigorous quality control, preprocessing, and integration steps to ensure a high-quality reference for annotation. scPANDA utilizes a three-layer inference approach, progressively refining cell types from broad compartments to specific clusters. Iterative clustering and harmonization processes were employed to maintain cell type purity throughout the analysis. Furthermore, the performance of scPANDA was evaluated in three external datasets. RESULTS: The atlas was structured hierarchically, consisting of 16 compartments, 54 classes, 4,‍460 low-level clusters (pd_cc_cl_tfs), and 611 high-level clusters (pmid_cts). Robust performance of the tool was demonstrated in annotating diverse immune scRNA-seq datasets, analyzing immune-tumor coexisting clusters in renal cell carcinoma, and identifying conserved cell clusters across species. CONCLUSIONS scPANDA exemplifies effective reference mapping with a large-scale atlas, enhancing the accuracy and reliability of blood cell type identification.
Humans ; Single-Cell Analysis/methods* ; Sequence Analysis, RNA/methods* ; Blood Cells

The spatio-temporal heterogeneity of breast cell subsets forms the fundamental biological basis for physiological development and pathological progression, including tumorigenesis; however, its complex regulatory mechanisms are not yet fully elucidated. With its high-resolution capabilities, single-cell RNA sequencing (scRNA-seq) technology offers a powerful tool for dissecting this cellular heterogeneity. This technology enables the construction of high-precision breast cell atlases, the accurate identification of distinct cell subsets, and the reconstruction of differentiation trajectories from stem/progenitor cells to functional epithelial cells. By resolving the transcriptional regulatory networks that govern cell fate determination, intercellular communication patterns, and dynamic microenvironmental interactions, scRNA-seq has unveiled the molecular foundations of breast development and provided new perspectives on the pathogenesis of related diseases such as breast cancer and macromastia. Furthermore, scRNA-seq demonstrates significant potential for discovering early molecular markers of disease, deciphering tumor heterogeneity, and elucidating mechanisms of therapeutic resistance. The continued application of scRNA-seq for dissecting breast cell heterogeneity, combined with its integration with multi-modal data such as spatial omics, promises to provide critical evidence and new insights for revealing the molecular mechanisms of breast development-related diseases and for formulating precision therapeutic strategies.
Humans ; Single-Cell Analysis/methods* ; Female ; Breast Neoplasms/pathology* ; Sequence Analysis, RNA/methods* ; Breast/cytology*

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve a comprehensive understanding of complex microbial communities together with their hosts are therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive response states among species in Prevotella and Roseburia genera and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.
Humans ; Gastrointestinal Microbiome/genetics* ; Bacteriophages/physiology* ; High-Throughput Nucleotide Sequencing ; Sequence Analysis, RNA/methods* ; Bacteria/virology*

Spinal cord injury (SCI) represents a complex pathophysiological process involving the interaction of multiple cell types. Conventional sequencing methods can only detect the average gene expression level of the damaged local cell populations, which is difficult to reflect its heterogeneity. Therefore, new technologies are needed to reveal the intercellular heterogeneity and the complex intercellular interactions of the damaged lesions. The single-cell RNA sequencing (scRNA-seq) technique facilitates high-resolution profiling of gene expression at the single-cell level, providing insights into cellular heterogeneity and function, potential molecular pathways, cell fate transitions, and the intercellular interactions pertinent to disease progression. This technology generates valuable gene expression data that support both basic and translational research efforts aiming at the identification of therapeutic targets for intervention. The scRNA-seq technique and its multifaceted application in the local immune microenvironment of injury after SCI were discussed, which will contribute to a more comprehensive understanding of the pathophysiological processes in the immune microenvironment of SCI.
Spinal Cord Injuries/genetics* ; Humans ; Single-Cell Analysis/methods* ; Sequence Analysis, RNA/methods* ; Animals ; Gene Expression Profiling/methods* ; Cellular Microenvironment/genetics*

OBJECTIVE: To depict the cell landscape and molecular biological characteristics of human intrauterine adhesion (IUA) so as to better understand its immune microenvironment and provide new inspirations for clinical treatment. METHODS: Four patients with IUA who underwent hysteroscopic treatment at Dongguan Maternal and Child Health Care Hospital from February 2022 to April 2022 were selected as the study subjects. Hysteroscopy was used to collect the tissues of IUA, which were graded based on the patient's medical history, menstrual history and status of IUA. Library construction, sequencing, single cell data comparison and gene expression matrix construction were carried out in strict accordance with the single cell RNA sequencing process. Thereafter, the UMAP dimension reduction analysis of cell population and genetic analysis were carried out based on the cell types. RESULTS: A total of 27 511 cell transcripts were obtained from four moderately graded IUA tissue samples and assigned to six cell lineages including T cells, mononuclear phagocytes, epithelial cells, fibroblasts, endothelial cells and erythrocytes. Compared with normal uterine tissue cells, the four samples showed different cell distribution, and the proportions of mononuclear phagocytes and T cells in sample IUA0202204 were significantly increased, suggesting a strong cellular immune response. CONCLUSION The cell diversity and heterogeneity of moderate IUA tissues have been described. Each cell subgroup has unique molecular characteristics, which may provide new clues for further study of the pathogenesis of IUA and heterogeneity among the patients.
Pregnancy ; Female ; Child ; Humans ; Endothelial Cells ; Uterine Diseases/complications* ; Hysteroscopy/methods* ; Tissue Adhesions/etiology* ; Sequence Analysis, RNA

Transcriptome analysis based on high-throughput sequencing of a cDNA library has been widely applied to functional genomic studies. However, the cDNA dependence of most RNA sequencing techniques constrains their ability to detect base modifications on RNA, which is an important element for the post-transcriptional regulation of gene expression. To comprehensively profile the N⁶-methyladenosine (m⁶A) and N⁵-methylcytosine (m⁵C) modifications on RNA, direct RNA sequencing (DRS) using the latest Oxford Nanopore Technology was applied to analyze the transcriptome of six tissues in rice. Approximately 94 million reads were generated, with an average length ranging from 619 nt to 1013 nt, and a total of 45,707 transcripts across 34,763 genes were detected. Expression profiles of transcripts at the isoform level were quantified among tissues. Transcriptome-wide mapping of m⁶A and m⁵C demonstrated that both modifications exhibited tissue-specific characteristics. The transcripts with m⁶A modifications tended to be modified by m⁵C, and the transcripts with modifications presented higher expression levels along with shorter poly(A) tails than transcripts without modifications, suggesting the complexity of gene expression regulation. Gene Ontology analysis demonstrated that m⁶A- and m⁵C-modified transcripts were involved in central metabolic pathways related to the life cycle, with modifications on the target genes selected in a tissue-specific manner. Furthermore, most modified sites were located within quantitative trait loci that control important agronomic traits, highlighting the value of cloning functional loci. The results provide new insights into the expression regulation complexity and data resource of the transcriptome and epitranscriptome, improving our understanding of the rice genome.
RNA ; Oryza/genetics* ; RNA, Messenger ; Gene Expression Profiling ; Transcriptome ; Sequence Analysis, RNA ; High-Throughput Nucleotide Sequencing/methods* ; RNA Processing, Post-Transcriptional